Ashwin Carvalho

1.5k total citations
18 papers, 1.1k citations indexed

About

Ashwin Carvalho is a scholar working on Automotive Engineering, Control and Systems Engineering and Social Psychology. According to data from OpenAlex, Ashwin Carvalho has authored 18 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Automotive Engineering, 16 papers in Control and Systems Engineering and 2 papers in Social Psychology. Recurrent topics in Ashwin Carvalho's work include Autonomous Vehicle Technology and Safety (13 papers), Vehicle Dynamics and Control Systems (11 papers) and Real-time simulation and control systems (9 papers). Ashwin Carvalho is often cited by papers focused on Autonomous Vehicle Technology and Safety (13 papers), Vehicle Dynamics and Control Systems (11 papers) and Real-time simulation and control systems (9 papers). Ashwin Carvalho collaborates with scholars based in United States, Türkiye and Sweden. Ashwin Carvalho's co-authors include Francesco Borrelli, Stéphanie Lefèvre, Georg Schildbach, Yiqi Gao, H. Eric Tseng, Jason Kong, Andrew Gray, Karl Henrik Johansson, Hongtei Eric Tseng and Valerio Turri and has published in prestigious journals such as IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Automation Science and Engineering and Vehicle System Dynamics.

In The Last Decade

Ashwin Carvalho

18 papers receiving 1.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ashwin Carvalho United States 16 841 708 242 122 122 18 1.1k
Mariana Netto France 17 1.0k 1.2× 924 1.3× 255 1.1× 137 1.1× 131 1.1× 56 1.5k
Xiaolin Song China 17 578 0.7× 423 0.6× 186 0.8× 202 1.7× 164 1.3× 70 1.0k
Duanfeng Chu China 17 673 0.8× 479 0.7× 224 0.9× 104 0.9× 164 1.3× 75 1.0k
Yiqi Gao United States 15 910 1.1× 742 1.0× 367 1.5× 90 0.7× 59 0.5× 20 1.2k
Pongsathorn Raksincharoensak Japan 21 847 1.0× 490 0.7× 244 1.0× 208 1.7× 273 2.2× 121 1.2k
Jinxiang Wang China 20 888 1.1× 635 0.9× 210 0.9× 91 0.7× 61 0.5× 91 1.2k
Haotian Cao China 17 518 0.6× 406 0.6× 153 0.6× 196 1.6× 144 1.2× 51 898
Yimin Chen China 16 517 0.6× 526 0.7× 192 0.8× 47 0.4× 57 0.5× 54 900
Andreas Eidehall Sweden 15 571 0.7× 284 0.4× 196 0.8× 94 0.8× 194 1.6× 19 824
Christian Pek Germany 15 585 0.7× 361 0.5× 257 1.1× 92 0.8× 136 1.1× 36 839

Countries citing papers authored by Ashwin Carvalho

Since Specialization
Citations

This map shows the geographic impact of Ashwin Carvalho's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ashwin Carvalho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashwin Carvalho more than expected).

Fields of papers citing papers by Ashwin Carvalho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ashwin Carvalho. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ashwin Carvalho. The network helps show where Ashwin Carvalho may publish in the future.

Co-authorship network of co-authors of Ashwin Carvalho

This figure shows the co-authorship network connecting the top 25 collaborators of Ashwin Carvalho. A scholar is included among the top collaborators of Ashwin Carvalho based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ashwin Carvalho. Ashwin Carvalho is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Shin, Dong-Hoon, Beomjun Kim, Kyongsu Yi, Ashwin Carvalho, & Francesco Borrelli. (2018). Human-Centered Risk Assessment of an Automated Vehicle Using Vehicular Wireless Communication. IEEE Transactions on Intelligent Transportation Systems. 20(2). 667–681. 51 indexed citations
2.
Schildbach, Georg, et al.. (2017). Scenario Model Predictive Control for Lane Change Assistance and Autonomous Driving on Highways. IEEE Intelligent Transportation Systems Magazine. 9(3). 23–35. 103 indexed citations
3.
Carvalho, Ashwin, et al.. (2017). Modeling, Identification, and Predictive Control of a Driver Steering Assistance System. IEEE Transactions on Human-Machine Systems. 47(5). 700–710. 29 indexed citations
4.
Carvalho, Ashwin, et al.. (2017). A machine learning approach for personalized autonomous lane change initiation and control. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 83 indexed citations
5.
Carvalho, Ashwin, et al.. (2017). A predictive control framework for torque-based steering assistance to improve safety in highway driving. Vehicle System Dynamics. 56(5). 810–831. 40 indexed citations
6.
Carvalho, Ashwin. (2016). Predictive Control under Uncertainty for Safe Autonomous Driving: Integrating Data-Driven Forecasts with Control Design. eScholarship (California Digital Library). 5 indexed citations
7.
Lefèvre, Stéphanie, Ashwin Carvalho, & Francesco Borrelli. (2015). Autonomous car following: A learning-based approach. 920–926. 51 indexed citations
8.
Claussmann, Laurène, Ashwin Carvalho, & Georg Schildbach. (2015). A path planner for autonomous driving on highways using a human mimicry approach with Binary Decision Diagrams. 2976–2982. 16 indexed citations
9.
Lefèvre, Stéphanie, Ashwin Carvalho, & Francesco Borrelli. (2015). A Learning-Based Framework for Velocity Control in Autonomous Driving. IEEE Transactions on Automation Science and Engineering. 13(1). 32–42. 161 indexed citations
10.
Liu, Changchun, Ashwin Carvalho, Georg Schildbach, & J. Karl Hedrick. (2015). Stochastic predictive control for lane keeping assistance systems using a linear time-varying model. 3355–3360. 20 indexed citations
11.
Carvalho, Ashwin, Stéphanie Lefèvre, Georg Schildbach, Jason Kong, & Francesco Borrelli. (2015). Automated driving: The role of forecasts and uncertainty—A control perspective. European Journal of Control. 24. 14–32. 120 indexed citations
12.
Lefèvre, Stéphanie, Ashwin Carvalho, Yiqi Gao, H. Eric Tseng, & Francesco Borrelli. (2015). Driver models for personalised driving assistance. Vehicle System Dynamics. 53(12). 1705–1720. 90 indexed citations
13.
Nilsson, Julia, Yiqi Gao, Ashwin Carvalho, & Francesco Borrelli. (2014). Manoeuvre generation and control for automated highway driving. IFAC Proceedings Volumes. 47(3). 6301–6306. 43 indexed citations
14.
Gao, Yiqi, Andrew Gray, Ashwin Carvalho, H. Eric Tseng, & Francesco Borrelli. (2014). Robust nonlinear predictive control for semiautonomous ground vehicles. 4913–4918. 26 indexed citations
15.
Turri, Valerio, Ashwin Carvalho, Hongtei Eric Tseng, Karl Henrik Johansson, & Francesco Borrelli. (2013). Linear model predictive control for lane keeping and obstacle avoidance on low curvature roads. KTH Publication Database DiVA (KTH Royal Institute of Technology). 378–383. 94 indexed citations
16.
Carvalho, Ashwin, Yiqi Gao, Andrew Gray, H. Eric Tseng, & Francesco Borrelli. (2013). Predictive control of an autonomous ground vehicle using an iterative linearization approach. 2335–2340. 93 indexed citations
17.
Carvalho, Ashwin, Giovanni Filippo Palmieri, H. Eric Tseng, Luigi Glielmo, & Francesco Borrelli. (2013). Robust vehicle stability control with an uncertain driver model. 440–445. 12 indexed citations
18.
Vyasarayani, C. P., Thomas K. Uchida, Ashwin Carvalho, & John McPhee. (2011). Parameter identification in dynamic systems using the homotopy optimization approach. Multibody System Dynamics. 26(4). 411–424. 40 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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